CN110177061B - Coordination method for signal interference in heterogeneous network - Google Patents
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Abstract
The invention provides a coordination method of signal interference in a heterogeneous network, which comprises cell sequencing and selection, interference signal rough estimation, interference elimination based on an iteration control table, interference signal reconstruction and elimination, wherein an ICCT (iterative interference control computer) based on the iteration elimination control table is adopted to replace a traditional iteration structure, and the calculation complexity can be greatly reduced under the condition of not influencing the discrimination performance.
Description
Technical Field
The invention relates to the technical field of communication, in particular to a coordination method for signal interference in a heterogeneous network.
Background
With the development of mobile internet and smart terminals and the evolution of UMTS system, high Speed Downlink Packet Access (HSDPA) technology has become an important means for enhancing the link performance of UMTS system. The heterogeneous network (Het-Net) technology is a technology for splitting cells and isomerizing a network structure, namely, a hierarchical network is established to deal with the surge of data traffic and meet the requirement of capacity increase. In a communication cellular network, a large number of low-power nodes, such as Pico (Pico) nodes, home (Femto) nodes, relay (Relay) nodes and the like, are arranged between a base station (eNB) and a User (UE) to realize signal forwarding, increase cell load and improve system performance. While edge users of a Pico base station deployed under the coverage of a macro base station (Marco) are interfered by downlink signals from the Marco base station, the performance is poor, and a certain downlink signal interference coordination strategy needs to be adopted to improve the performance of the edge users of the cell.
Aiming at the characteristics of the heterogeneous network, the invention mainly researches the cell interference suppression algorithm in the heterogeneous network, which comprises the following steps: starting from a traditional CS/CB scheme, the traditional CRS-IC method is an iterative structure, and in the interference elimination process, in order to obtain good interference elimination capability, the iteration times are high. In order to reduce the computational complexity due to algorithm iteration, the traditional better approach is to use a real-time iteration stop criterion. The real-time iteration stopping criterion needs real-time calculation based on a certain loss function, whether to stop iteration is judged according to the calculation result,
compared with the existing scheme, the invention provides an improved scheme aiming at the condition of high system complexity of the original scheme, and performs system simulation and performance analysis on the scheme, so that the scheme can greatly reduce the system complexity under the condition of ensuring less system performance loss.
Disclosure of Invention
The invention aims to provide a method for coordinating signal interference in a heterogeneous network, which is characterized by comprising the following steps:
s10: cell sorting and selection;
s20: roughly estimating interference signals;
s30: interference cancellation based on an iterative control table;
s40: reconstructing and eliminating interference signals;
preferably, the S10 includes the steps of:
cell sorting;
s11: the signals received by the user terminal comprise signals transmitted from all interference cells and the service cell, all cells are sequenced according to the field intensity of each received cell signal, and the stronger the field intensity of the received signals is, the more forward the sequencing is.
S12: and selecting the signal with stronger field intensity to estimate, reconstruct and eliminate, and then processing the signal with weaker received signal intensity.
When the selected signal field strength is stronger, the signal receiving signal-to-noise ratio is higher, and the result in signal processing is more accurate. Interference cancellation will start with the signal with the strongest received signal strength
Preferably, the S20 includes the following steps
S21: generating a local CRS signal according to the cell ID and the antenna port;
s22: based on the LS method, the coarse channel estimation of the CRS position is calculated by using the local CRS signal and the received CRS receiving signal, and the channel estimation formula is as follows:
wherein the interference part is:
here, the
Is the result of coarse channel estimation at CRS position, (k ', l ') represents the kth CRS subcarrier at the l ' th OFDM symbol.
S30: interference cancellation based on an iterative cancellation control table;
preferably, the S30 includes the steps of:
the method comprises the following 3 steps:
s31: an ICCT is generated off-line and is a three-dimensional lookup table, and indexes of three dimensions are a coding and debugging Mode (MCS), a Time Delay Spread (TDS) and an initial signal to interference plus noise ratio (SINR) respectively;
s32: in the interference elimination iteration process, searching an ICCT according to the three indexes, wherein the ICCT outputs iteration times and an SINR updating step length, the iteration times are used for controlling the stop of interference elimination iteration, and the SINR updating step length is used for SINR calculation;
s40: reconstructing and eliminating interference signals;
preferably, the S40 includes 3 steps:
s41: selecting a smoothing filter coefficient according to TDS and SINR found from ICCT in an iterative process, and filtering an obtained rough channel estimation result of the CRS position;
s42: reconstructing the received cell CRS signal by using the local CRS signal and the obtained channel estimation result after smooth filtering;
s43: subtracting the reconstructed CRS signal from the received signal;
the invention has the advantages that:
the invention solves the defect of high calculation complexity in the traditional iteration stopping method, provides an interference coordination method based on an iteration elimination control table (ICCT), obtains iteration times and required parameters under different conditions through intermediate results in an iteration process according to a preset ICCT table, and can determine whether to stop the iteration processing of interference elimination only through table lookup. By the method and the device, the balance between iteration times and performance can be achieved by using lower calculation complexity.
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FIG. 1 is a flow chart of an embodiment of the present invention;
FIG. 2 is a simulation test chart of an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The invention aims to provide a method for coordinating signal interference in a heterogeneous network, which mainly comprises the following steps:
s10: cell sorting and selecting;
wherein, S10: the cell sequencing includes that signals transmitted from all interference cells and serving cells are contained in signals received by the terminal. And sequencing all the cells according to the received field intensity of each cell signal, wherein the stronger the field intensity of the received signals is, the more the ranking is forward. The stronger the field strength of the signal, the higher the received signal-to-noise ratio, the more accurate the result will be in signal processing. The interference cancellation will start with estimating, reconstructing and canceling the signal with the strongest received signal strength, and then process the signal with the weaker received signal strength.
S20: roughly estimating interference signals;
the method comprises the following two steps S21 and S22:
s21: generating a local CRS signal according to the cell ID and the antenna port;
s22: based on the LS method, calculating coarse channel estimation of the CRS position by using a local CRS signal and a received CRS receiving signal;
wherein the interfering part is
Here, the
Is the result of coarse channel estimation at CRS position, (k ', l ') represents the kth CRS subcarrier at the l ' OFDM symbol.
S30: interference cancellation based on an iterative control table;
the method comprises the following 3 steps:
an ICCT is generated off-line and is a three-dimensional lookup table, and indexes of three dimensions are a coding and debugging Mode (MCS), a Time Delay Spread (TDS) and an initial signal-to-interference-plus-noise ratio (SINR) respectively.
In the interference elimination iteration process, the ICCT is searched according to the three indexes, the ICCT outputs iteration stop times and SINR updating step length, the iteration times are used for interference elimination iteration control, and the SINR updating step length is used for SINR calculation.
For example, for an ICCT table [ i ] of 9x12x4 MCS ,i ISINR ,i TDS ]During each iteration, the search of the ICCT table is performed using 3 index parameters according to the following formula:
in the interference elimination process, the performance of the interference elimination process depends on the performance of the smoothing filter, and the performance of the smoothing filter is determined by two parameters, namely TDS and SINR, so the TDS and SINR can be used as two indexes of the ICCT. In addition, to improve the iteration efficiency of the algorithm under different MCSs, we also introduce an MCS as a third index. When the MCS is low, a lower number of iterations is sufficient, which may further reduce the computational complexity.
S40: reconstructing and eliminating interference signals;
comprises 3 steps:
s41: selecting a smoothing filter coefficient according to TDS and SINR found from ICCT in an iterative process, and filtering an obtained rough channel estimation result of the CRS position;
s42: reconstructing the received cell CRS signal by using the local CRS signal and the obtained channel estimation result after smooth filtering;
s43: the reconstructed CRS signal is subtracted from the received signal.
The wireless communication environment is very complex, the wireless communication system is also very huge, and in order to measure the system performance, it is a common means to adopt the simulation technology to perform system simulation. The performance of the system can be obtained by reasonably setting a simulation environment and designing related parameters, and the simulation technology is mainly divided into link-level simulation and system-level simulation;
the system level simulation comprises static simulation and dynamic simulation, wherein the static simulation refers to obtaining the average performance of a system through a snapshot of the system simulation, namely a Monte Carlo method; dynamic simulation is to simulate the mobility of a user, and the system performance is obtained through a certain snapshot in consideration of the switching from the user to a base station. However, the calculation of the static simulation is relatively simple, the consumed time is relatively short, and the stability is higher, so that although the dynamic simulation is closer to the actual situation, the static simulation can also ensure the reliability of the network performance analysis through the statistics of the snapshot at different times.
CRS is designed in LTE for channel estimation and channel quality measurement, and for both PDSCH and PDCCH and PBCH, CRS is used for channel estimation, another role of CRS is to determine user reselection and handover between cells, users measure power on CRS sent by different base stations, and handover occurs when RSRP (reference signal received power) of their serving base station is found to be less than RSRP from neighboring base station to user for a period of time.
In consideration of the complexity of the CRS-IC receiver, a receiver other than the CRS-IC receiver is usually considered to demodulate PDSCH signals, and in the LTE system, users in the CRE region in the micro base station cell may use the CRS-IC receiver to demodulate PBCH and PSS/SSS because the system has high requirements for demodulation of PBCH and PSS/SSS, and there is no PDSCH long relative to the decoding period of PBCH and PSS/SSS, which has relatively small influence on power consumption.
The CRS-IC receiver assumes that the UE has strong decoding capability, if the UE in the micro base station cell can decode the CRS sequence with large interference to the UE first, and then remove the CRS interference, the decoded SINR can be greatly improved. Moreover, since the UE can demodulate the CRS sequence in multiple subframes, the decoding accuracy of the user on the CRS sequence with large interference is still high.
Please refer to fig. 1, which is a schematic diagram of an implementation flow of CRS-IC according to the present invention.
To evaluate the performance of interference cancellation, simulations were performed using the following scenario:
there are several points to be explained about simulation:
firstly, suppose that a user is static, namely, a service cell of the user is unchanged, and the problem of switching is not involved;
secondly, the backhaul link is ideal, namely, the time delay of information interaction between base stations is not considered;
thirdly, the simulation results include throughput, received signal-to-noise ratio, curves, etc., and the values are derived from the average of the performance of all users successfully transmitting data in the simulation. Therefore, the accuracy of the statistical result is related to factors such as simulation duration, user arrival rate, data bit size and the like;
fourthly, the process that the users enter the system obeys Poisson distribution, and the time intervals of the two adjacent users obey exponential distribution. Once the user's packet is delivered, the user leaves the system.
The simulation parameters are as follows:
1)TM2,2x2_low,BW＝10MHz
2)MCS8
3)SNR＝-5:5dB,SIR＝-12dB
4) Frequency band/bandwidth of 2.6GHz,20MHz
5) Path loss COST-Hata
6) Receiver model MMSE-IRC/MRC
7) Link adaptive AMC
8) Simulation duration 3000TTI
Referring to fig. 2, the performance of the CRS-IC method based on ICCT proposed by the present invention is very close to that of the method based on the real-time stop criterion discrimination under different snr and different signal types.
When the calculation complexity is compared, the calculation complexity of the ICCT-based CRS-IC method and the real-time stop criterion discrimination method is compared as shown in the following table, and the calculation complexity of the ICCT-based CRS-IC method is obviously reduced through a comparison result.
The above description is only exemplary of the present invention, and the structure is not limited to the above-mentioned shapes, and any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (2)
1. A method for coordinating signal interference in a heterogeneous network, comprising,
s10: cell sorting and selection;
s20: roughly estimating interference signals;
s30: interference cancellation based on an iterative control table;
s40: reconstructing and eliminating interference signals;
said S10 comprises the steps of,
s11: the signals received by the user terminal comprise signals transmitted from all interference cells and service cells, all the cells are sorted according to the field intensity of each received cell signal, and the stronger the field intensity of the received signals is, the more forward the sorting is;
s12: selecting signals with stronger field intensity to estimate, reconstruct and eliminate, and then processing the signals with weak received signal intensity;
the S20 includes the steps of,
s21: generating a local CRS signal according to the cell ID and the antenna port;
s22: based on the LS method, calculating a coarse channel estimate of the CRS position by using a local CRS signal and a received CRS receiving signal;
the coarse channel estimation formula for the CRS positions is,
wherein the interference part is:
here, the
Coarse channel estimate as a function of CRS position, (k ', l ') represents at l 'A kth CRS subcarrier of a number of OFDM symbols;
the S30 includes the steps of,
s31: generating an iterative cancellation control table ICCT offline;
s32: in the interference elimination iteration process, searching an iteration elimination control table ICCT according to indexes in the iteration elimination control table ICCT to obtain iteration parameters of corresponding indexes for interference elimination iteration control;
the ICCT is a three-dimensional lookup table, and indexes of three dimensions are respectively a coding and debugging mode MCS, a time delay spread TDS and an initial signal to interference plus noise ratio SINR;
in the interference elimination iteration process, searching an ICCT according to the three indexes, wherein the ICCT outputs iteration stop times and an SINR updating step length, the iteration times are used for interference elimination iteration control, and the SINR updating step length is used for SINR calculation;
the S40 includes the steps of,
s41: selecting a smoothing filter coefficient according to the time delay spread TDS and the initial signal to interference plus noise ratio SINR searched from ICCT in the iterative process, and filtering the obtained coarse channel estimation result of the CRS position;
s42: reconstructing the received cell CRS signal by using the local CRS signal and the obtained channel estimation result after smooth filtering;
s43: the reconstructed CRS signal is subtracted from the received signal.
2. The method of claim 1, wherein the ICCT is a two-dimensional lookup table, and the two-dimensional indices are a delay spread TDS and an initial signal-to-interference-and-noise ratio SINR, respectively.
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